Model contribution margin, CAC payback, and LTV for a startup
A clean analytics dashboard or notebook with business question, dataset, metrics, insights, and decision recommendation.
Open full project briefWhat to do
You are working as a Venture Capital. Your manager asks you to use Unit Economics to answer a real business or investment question and present a decision-ready output.
Show that you can apply Unit Economics in a practical analyst workflow, not only explain the theory.
- Define the business question and stakeholder.
- Create or source a dataset with a data dictionary.
- Choose 5-8 metrics that answer the question.
- Clean data and document assumptions.
- Create SQL queries or Python transformations.
- Build visualizations for trend, mix, cohort, funnel, and exception analysis.
- Write insights and recommended actions.
- Package the final output so someone can read it without your explanation.
- Brief
- Model or notebook
- Charts or dashboard
- Resume bullet
- Source and assumption log
- One-page executive summary
- Final output file
- Public Kaggle-style dataset
- Synthetic transaction dataset
- Company metrics from filings
- RBI/NPCI public statistics
- Open government data
- Metric definitions are clear.
- Charts answer real business questions.
- Data quality issues are documented.
- Insights lead to decisions.
- Dashboard avoids clutter and vanity metrics.
- Problem: explain the business question and why it matters for Venture Capital.
- Method: describe the data collected, assumptions made, and analysis performed.
- Decision: state the recommendation, key risk, and what would change your view.
Built a a clean analytics dashboard or notebook with business question, dataset, metrics, insights, and decision recommendation. for Unit Economics, using Spreadsheet to convert raw information into a decision-ready finance output.


